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Int J Epidemiol. 2003 Aug;32(4):518-26.

The World Health Organization Global Database on Child Growth and Malnutrition: methodology and applications.

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1
Department of Nutrition for Health and Development, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland. deonis@who.int

Abstract

BACKGROUND:

For decades nutritional surveys have been conducted using various definitions, indicators and reference populations to classify child malnutrition. The World Health Organization (WHO) Global Database on Child Growth and Malnutrition was initiated in 1986 with the objective to collect, standardize, and disseminate child anthropometric data using a standard format.

METHODS:

The database includes population-based surveys that fulfil a set of criteria. Data are checked for validity and consistency and raw data sets are analysed following a standard procedure to obtain comparable results. Prevalences of wasting, stunting, under- and overweight in preschool children are presented using z-scores based on the National Center for Health Statistics (NCHS)/WHO international reference population. New surveys are included on a continuous basis and updates are published bimonthly on the database's web site.

RESULTS:

To date, the database contains child anthropometric information derived from 846 surveys. With 412 national surveys from 138 countries and 434 sub-national surveys from 155 countries, the database covers 99% and 64% of the under 5 year olds in developing and developed countries, respectively. This wealth of information enables international comparison of nutritional data, helps identifying populations in need, evaluating nutritional and other public health interventions, monitoring trends in child growth, and raising political awareness of nutritional problems.

CONCLUSIONS:

The 15 years experience of the database can be regarded as a success story of international collaboration in standardizing child growth data. We recommend this model for monitoring other nutritional health conditions that as yet lack comparable data.

PMID:
12913022
[Indexed for MEDLINE]
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